Belajar Hubungan Intensitas Penggunaan ChatGPT dengan Hasil Mahasiswa
DOI:
https://doi.org/10.57235/jerumi.v4i1.8592Keywords:
Intensitas Penggunaan ChatGPT; Hasil Belajar; Mahasiswa; Kecerdasan Buatan; Korelasi PearsonAbstract
Perkembangan teknologi kecerdasan buatan, khususnya ChatGPT, telah membawa perubahan mendasar dalam pola belajar mahasiswa. Penelitian ini bertujuan untuk: (1) mendeskripsikan gambaran intensitas penggunaan ChatGPT di kalangan mahasiswa, (2) mendeskripsikan gambaran hasil belajar mahasiswa, dan (3) menganalisis hubungan antara intensitas penggunaan ChatGPT dengan hasil belajar mahasiswa. Penelitian menggunakan pendekatan kuantitatif dengan metode korelasional deskriptif. Populasi penelitian adalah mahasiswa aktif Universitas Negeri Jakarta semester genap 2024/2025, dengan sampel 120 mahasiswa yang dipilih menggunakan teknik purposive sampling. Instrumen penelitian berupa kuesioner intensitas penggunaan ChatGPT (25 butir, skala Likert 1–5, α = 0,891) yang mencakup empat dimensi: frekuensi, durasi, kedalaman interaksi, dan tujuan penggunaan; serta data hasil belajar berupa Indeks Prestasi Semester (IPS). Uji prasyarat meliputi uji normalitas Kolmogorov-Smirnov dan uji linearitas. Analisis data menggunakan korelasi Pearson Product Moment dengan bantuan SPSS 26. Hasil penelitian menunjukkan: (1) rata-rata skor intensitas penggunaan ChatGPT sebesar 82,45 (kategori sedang-tinggi), (2) rata-rata IPS mahasiswa sebesar 3,28 (kategori baik), dan (3) terdapat hubungan yang positif dan signifikan antara intensitas penggunaan ChatGPT dengan hasil belajar mahasiswa (r = 0,612; r tabel = 0,179; p = 0,000 < 0,05) dengan koefisien determinasi sebesar 37,4%. Temuan ini mengindikasikan bahwa pemanfaatan ChatGPT secara terstruktur, terarah, dan kritis berkontribusi positif terhadap pencapaian akademik mahasiswa.
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References
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T
Anderson, L. W., & Krathwohl, D. R. (Eds.). (2001). A taxonomy for learning, teaching, and assessing: A revision of Bloom's taxonomy of educational objectives. Longman.
Baidoo-Anu, D., & Ansah, L. O. (2023). Education in the era of generative artificial intelligence (AI): Understanding the potential benefits of ChatGPT in promoting teaching and learning. Journal of AI, 7(1), 52–62. https://doi.org/10.61969/jai.1337500
Biggs, J., & Tang, C. (2011). Teaching for quality learning at university (4th ed.). Open University Press.
Bloom, B. S. (1984). The 2 sigma problem: The search for methods of group instruction as effective as one-to-one tutoring. Educational Researcher, 13(6), 4–16. https://doi.org/10.3102/0013189X013006004
Bloom, B. S., Engelhart, M. D., Furst, E. J., Hill, W. H., & Krathwohl, D. R. (1956). Taxonomy of educational objectives: The classification of educational goals. Handbook I: Cognitive domain. David McKay.
Brandtzaeg, P. B., & Heim, J. (2011). A typology of social networking sites users. International Journal of Web Based Communities, 7(1), 28–51. https://doi.org/10.1504/IJWBC.2011.038124
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum Associates.
Cotton, D. R. E., Cotton, P. A., & Shipway, J. R. (2023). Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Innovations in Education and Teaching International, 61(2), 228–239. https://doi.org/10.1080/14703297.2023.2190148
Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). SAGE Publications.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
Dempere, J., Modugu, K., Hesham, A., & Ramasamy, L. K. (2023). The impact of ChatGPT on higher education. Frontiers in Education, 8, 1206936. https://doi.org/10.3389/feduc.2023.1206936
Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2012). How to design and evaluate research in education (8th ed.). McGraw-Hill.
George, D., & Mallery, P. (2003). SPSS for Windows step by step: A simple guide and reference, 11.0 update (4th ed.). Allyn & Bacon.
Hattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77(1), 81–112. https://doi.org/10.3102/003465430298487
Hu, K. (2023, February 2). ChatGPT sets record for fastest-growing user base. Reuters. https://www.reuters.com/technology/chatgpt-sets-record-fastest-growing-user-base-analyst-note-2023-02-01/
Kasneci, E., Sessler, K., Kuchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Gunnemann, S., Hullermeier, E., Krusche, S., Kutyniok, G., Michaeli, T., Nemmert, C., Nie, F., Razniewski, S., Schwingel, M., & Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274
Katz, E., Blumler, J. G., & Gurevitch, M. (1974). Utilization of mass communication by the individual. In J. G. Blumler & E. Katz (Eds.), The uses of mass communications: Current perspectives on gratifications research (pp. 19–32). SAGE Publications.
Kuh, G. D., Kinzie, J., Buckley, J. A., Bridges, B. K., & Hayek, J. C. (2006). What matters to student success: A review of the literature. National Postsecondary Education Cooperative.
Kuhail, M. A., Alturki, N., Alramlawi, S., & Alhejori, K. (2023). Interacting with educational chatbots: A systematic review. Education and Information Technologies, 28, 973–1018. https://doi.org/10.1007/s10639-022-11177-3
Labadze, L., Grigolia, M., & Machaidze, L. (2023). Role of AI chatbots in education: Systematic literature review. International Journal of Educational Technology in Higher Education, 20, 56. https://doi.org/10.1186/s41239-023-00426-1
OpenAI. (2023). GPT-4 technical report. arXiv. https://arxiv.org/abs/2303.08774
Ouyang, L., Wu, J., Jiang, X., Almeida, D., Wainwright, C. L., Mishkin, P., Zhang, C., Agarwal, S., Slama, K., Ray, A., Schulman, J., Hilton, J., Kelton, F., Miller, L., Simens, M., Askell, A., Welinder, P., Christiano, P., Leike, J., & Lowe, R. (2022). Training language models to follow instructions with human feedback. Advances in Neural Information Processing Systems, 35, 27730–27744.
Pardos, Z. A., & Bhandari, S. (2023). Learning gain differences between ChatGPT and human tutor generated hints. arXiv. https://arxiv.org/abs/2302.07726
Pascarella, E. T., & Terenzini, P. T. (2005). How college affects students: Vol. 2. A third decade of research. Jossey-Bass.
Polit, D. F., & Beck, C. T. (2006). The content validity index: Are you sure you know what's being reported? Critique and recommendations. Research in Nursing & Health, 29(5), 489–497. https://doi.org/10.1002/nur.20147
Statista. (2024). Countries with the most ChatGPT website visits worldwide as of January 2024. Statista Research Department. https://www.statista.com/statistics/1381238/chatgpt-website-visits-by-country/
Tlili, A., Shehata, B., Adarkwah, M. A., Bozkurt, A., Hickey, D. T., Huang, R., & Agyemang, B. (2023). What if the devil is my guardian angel: ChatGPT as a case study of using chatbots in education. Smart Learning Environments, 10, 15. https://doi.org/10.1186/s40561-023-00237-x
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified theory. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540
Warschauer, M., Tseng, W., Yim, S., Webster, T., Jacob, S., Du, Q., & Tate, T. (2023). The affordances and contradictions of AI-generated text for writers in higher education. Computers and Education: Artificial Intelligence, 5, 100166. https://doi.org/10.1016/j.caeai.2023.100166
Zhai, X., Chu, X., Chai, C. S., Jong, M. S. Y., Istenic, A., Spector, M., Liu, J.-B., Yuan, J., & Li, Y. (2024). A review of artificial intelligence (AI) in education from 2010 to 2020. Complexity, 2021, 8812542. https://doi.org/10.1155/2021/8812542
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